Evidence map›Paper›PMID 31782029›Full record

ArticleBiomechanics and modeling in mechanobiology2020

Network architecture strongly influences the fluid flow pattern through the lacunocanalicular network in human osteons.

Alexander F van Tol, A Roschger, F Repp, J Chen, P Roschger, A Berzlanovich, G M Gruber, P Fratzl, Richard Weinkamer

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In one paragraph

Article in Biomechanics and modeling in mechanobiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
6.6field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

23 citing papers in PubMed, 72 citations in OpenAlex.

  1. Article
  2. Bone matrix proteins: regulators of skeletal remodeling and repair.Journal of bone and mineral metabolism · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 5 institutions in 3 countries.

Alexander F van TolDepartment of Biomaterials, Max Planck Institute of Colloids and Interfaces, 14476, Potsdam, Germany. Alexander.VanTol@mpikg.mpg.de.ORCID http://orcid.org/0000-0003-2095-6213
A RoschgerDepartment of Biomaterials, Max Planck Institute of Colloids and Interfaces, 14476, Potsdam, Germany.ORCID http://orcid.org/0000-0003-0353-8239
F ReppDepartment of Biomaterials, Max Planck Institute of Colloids and Interfaces, 14476, Potsdam, Germany.ORCID http://orcid.org/0000-0003-0204-929X
J ChenDepartment of Biomaterials, Max Planck Institute of Colloids and Interfaces, 14476, Potsdam, Germany.ORCID http://orcid.org/0000-0001-7121-0994
P RoschgerLudwig Boltzmann Institute of Osteology at the Hanusch Hospital of WGKK and AUVA Trauma Centre Meidling, 1st Medical Department, Hanusch Hospital, Heinrich Collin Str. 30, 1140, Vienna, Austria.
A BerzlanovichCenter of Forensic Science, Medical University of Vienna, Sensengasse 2, 1090, Vienna, Austria.ORCID http://orcid.org/0000-0001-5276-1280
G M GruberDepartment of Anatomy, Center for Anatomy and Cell Biology, Medical University of Vienna, 1090, Vienna, Austria.ORCID http://orcid.org/0000-0001-7403-0788
P FratzlDepartment of Biomaterials, Max Planck Institute of Colloids and Interfaces, 14476, Potsdam, Germany.ORCID http://orcid.org/0000-0003-4437-7830
Richard WeinkamerDepartment of Biomaterials, Max Planck Institute of Colloids and Interfaces, 14476, Potsdam, Germany.ORCID http://orcid.org/0000-0002-3858-9047
Max Planck Institute of Colloids and Interfaces · DEMedical University of Vienna · ATHanusch Hospital · ATUniversity of Exeter · GBUniversity of Salzburg · AT

Funding

Deutsche Forschungsgemeinschaft WE 4341/1-1
6 · The paper itself

Abstract

A popular hypothesis explains the mechanosensitivity of bone due to osteocytes sensing the load-induced flow of interstitial fluid squeezed through the lacunocanalicular network (LCN). However, the way in which the intricate structure of the LCN influences fluid flow through the network is largely unexplored. We therefore aimed to quantify fluid flow through real LCNs from human osteons using a combination of experimental and computational techniques. Bone samples were stained with rhodamine to image the LCN with 3D confocal microscopy. Image analysis was then performed to convert image stacks into mathematical network structures, in order to estimate the intrinsic permeability of the osteons as well as the load-induced fluid flow using hydraulic circuit theory. Fluid flow was studied in both ordinary osteons with a rather homogeneous LCN as well as a frequent subtype of osteons-so-called osteon-in-osteons-which are characterized by a ring-like zone of low network connectivity between the inner and the outer parts of these osteons. We analyzed 8 ordinary osteons and 9 osteon-in-osteons from the femur midshaft of a 57-year-old woman without any known disease. While the intrinsic permeability was 2.7 times smaller in osteon-in-osteons compared to ordinary osteons, the load-induced fluid velocity was 2.3 times higher. This increased fluid velocity in osteon-in-osteons can be explained by the longer path length, needed to cross the osteon from the cement line to the Haversian canal, including more fluid-filled lacunae and canaliculi. This explanation was corroborated by the observation that a purely structural parameter-the mean path length to the Haversian canal-is an excellent predictor for the average fluid flow velocity. We conclude that osteon-in-osteons may be particularly significant contributors to the mechanosensitivity of cortical bone, due to the higher fluid flow in this type of osteons.

Indexed as

Imaging, Three-DimensionalBone and BonesFemaleFemurHaversian SystemHumansImage Processing, Computer-AssistedMicroscopy, ConfocalMiddle AgedModels, TheoreticalOsteocytesPermeabilityRhodaminesRhodaminesCanaliculiFluid flowHuman osteonLacunaLacunocanalicular networkOsteocyte

Identifiers

PMID31782029
PMCPMC7203595
OpenAlexW2991187435

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.